Pauly, L, Agboh, WC, Abdellatif, M et al. (2 more authors) (2018) One-Shot Observation Learning. [Preprint - arXiv]
Abstract
Observation learning is the process of learning a task by observing an expert demonstrator. We present a robust observation learning method for robotic systems. Our principle contributions are in introducing a one shot learning method where only a single demonstration is needed for learning and in proposing a novel feature extraction method for extracting unique activity features from the demonstration. Reward values are then generated from these demonstrations. We use a learning algorithm with these rewards to learn the controls for a robotic manipulator to perform the demonstrated task. With simulation and real robot experiments, we show that the proposed method can be used to learn tasks from a single demonstration under varying conditions of viewpoints, object properties, morphology of manipulators and scene backgrounds.
Metadata
Item Type: | Preprint |
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Authors/Creators: |
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Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/N010523/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Mar 2025 13:22 |
Last Modified: | 28 Mar 2025 13:22 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:138418 |